SRM 3252 Protein Drink Mix - This Standard Reference Material (SRM) is intended primarily for validation of methods for determining proximates, fatty acids, cholesterol, vitamins, elements, and amino acids in protein drink mixes and similar materials. This SRM can also be used for quality assurance when assigning values to in-house reference materials. This data is public in the Certificate of Analysis for this material.

SRM 3290 Dry Cat Food - This Standard Reference Material (SRM) is intended primarily for use in validating methods for determining proximates, fatty acids, vitamins, elements, and amino acids in dry cat food and similar matrices. This SRM can also be used for quality assurance when assigning values to in-house control materials. This SRM is a blend of commercially available dry cat foods. A unit of SRM 3290 consists of five heat-sealed, aluminized pouches, each containing approximately 10 g of material. This data is public in the Certificate of Analysis for this material.

Standard Reference Material 3949 Folate Vitamers in Frozen Human Serum

Standard Reference Material 909c Frozen Human Serum - This Standard Reference Material (SRM) is intended primarily for use in validating analytical methods for the determination of specified constituents in human serum. This SRM can also be used for quality assurance when assigning values to in house control materials. A unit of SRM 909c consists of three vials, each containing 2 mL of frozen human serum. This data is public in the Certificate of Analysis for this material.

SRM 972a Vitamin D Metabolites in Frozen Human Serum - This Standard Reference Material (SRM) is intended for use as an accuracy control in the critical evaluation of methods for determining the amount-of-substance concentration of vitamin D metabolites in human serum. This SRM can also be used as a quality assurance tool for assigning values to in-house control materials for these constituents. This data is public in the Certificate of Analysis for this material.

Using a modified Thomas-Fermi approximation, we model a reference semiconductor system comprising a quasi-1D nanowire with a series of five depletion gates whose voltages determine the number of quantum dots (QDs), the charges on each of the QDs, as well as the conductance through the wire. The original dataset, QFlow lite, consists of 1 001 idealized simulated measurements with gate configurations sampling over different realizations of the same type of device.

There is often a large amount of maintenance data already available for use in Smart Manufacturing systems, but in a currently-unusable form: service tickets and maintenance work orders (MWOs). Nestor is a toolkit for using Natural Language Processing (NLP) with efficient user-interaction to perform structured data extraction with minimal annotation time-cost.

The REsource for Materials Informatics (REMI) will host a diverse collection of scripting notebooks (Jupyter, Matlab LiveScripts, etc.) for collecting, pre-processing, analyzing, and visualizing materials data. Notebooks are curated using tags aligned to Materials Science and Data Science topics. REMI emerged from the realization that both experts and novices wanted examples of using machine learning for science. Meanwhile, lots of experts are developing digital notebooks (e.g. Jupyter) to demonstrate step-by-step data collection, pre-processing, analysis and visualization.

Atomic Bose-Einstein condensates (BECs) are widely investigated systems that exhibit quantum phenomena on a macroscopic scale. For example, they can be manipulated to contain solitonic excitations including conventional solitons, vortices, and many more. Broadly speaking, solitonic excitations are solitary waves that retain their size and shape and often propagate at a constant speed. They are present in many systems, at scales ranging from microscopic, to terrestrial and even astronomical.

The Inorganic Crystal Structure Database (ICSD) is produced cooperatively by the Fachinformationszentrum Karlsruhe (FIZ) and the National Institute of Standards and Technology (NIST). Components and devices used in a broad spectrum of technology sectors such as health care, communications, energy and electronics are manufactured from crystalline materials; the development of advanced crystalline materials requires accurate crystal-structure data.